code: def test_extractor(self):
      # data = ['Indeed, risk factors are sex, obesity, genetic factors and mechanical factors (3) .',
      #        'The sun is the center of our solar system.',
      #        'There is a risk of Donald Trump running again in 2024.',
      #        'My speciality is risk assessments.',
      #         """This risk was consistent across patients stratified by history of CVD, risk factors
      #         but no CVD, and neither CVD nor risk factors.""",
      #        """Risk factors associated with subsequent death include older age, hypertension, diabetes,
      #        ischemic heart disease, obesity and chronic lung disease; however, sometimes
      #         there are no obvious risk factors .""",
      #         'Three major risk factors for COVID-19 were sex (male), age (≥60), and severe pneumonia.']
      # from ktrain.text import AnswerExtractor
      # ae = AnswerExtractor()
      # import pandas as pd
      # pd.set_option("display.max_colwidth", None)
      # df = pd.DataFrame(data, columns=['Text'])
      # df = ae.extract(df.Text.values, df, [('What are the risk factors?', 'Risk Factors')], min_conf=8)
      # answers = df['Risk Factors'].values
      # self.assertEqual(answers[0].startswith('sex'), True)
      # self.assertEqual(answers[1], None)
      # self.assertEqual(answers[2], None)
      # self.assertEqual(answers[3], None)
      # self.assertEqual(answers[4], None)
      # self.assertEqual(answers[5].startswith('older'), True)
      # self.assertEqual(answers[6].startswith('sex'), True)
  
      data = [
          "Three major risk factors for COVID-19 were sex (male), age (≥60), and severe pneumonia.",
          "His speciality is medical risk assessments, and he is 30 years old.",
          "Results: A total of nine studies including 356 patients were included in this study, the mean age was 52.4 years and 221 (62.1%) were male.",
      ]
      from ktrain.text import AnswerExtractor
  
      ae = AnswerExtractor(framework="pt", device="cpu", quantize=True)
      import pandas as pd
  
      pd.set_option("display.max_colwidth", None)
      df = pd.DataFrame(data, columns=["Text"])
      import time
  
      start = time.time()
      df = ae.extract(
          df.Text.values,
          df,
          [
              ("What are the risk factors?", "Risk Factors"),
              ("How many individuals in sample?", "Sample Size"),
          ],
          min_conf=5,
      )
      print(time.time() - start)
      print(df.head())
      answers = df["Risk Factors"].values
      self.assertEqual(answers[0].startswith("sex"), True)
      self.assertEqual(answers[1], None)
      self.assertEqual(answers[2], None)
      answers = df["Sample Size"].values
      self.assertEqual(answers[0], None)
      self.assertEqual(answers[1], None)
      self.assertEqual(answers[2].startswith("356"), True)
  
file_path: ktrain/tests/test_qa.py
imports: from unittest import TestCase, main, skip
  import IPython
  import numpy
  import testenv
  import ktrain
  from ktrain import text
  from ktrain.imports import ACC_NAME, VAL_ACC_NAME
label_desc: Use image node_id 2 for calling the TestQA obj's underlying member method code with example usage: obj.test_extractor() without return types